Efficacy and Safety of Tinzaparin in CAT Patients with Hematological Malignancy
Bibliographic record
Abstract
Abstract Introduction In patients with hematological cancers, the high risk of bleeding raises serious concerns when anticoagulant therapy is initiated for treatment of acute venous thromboembolism (VTE). In the CATCH trial, we showed that tinzaparin is associated with a significantly lower risk of clinically relevant bleeding (CRB) and clinically relevant non-major bleeding (CRNMB) compared with warfarin therapy in patients with a solid tumor or hematological cancer. Hence, we performed a post-hoc analysis to assess the risk of recurrent VTE (rVTE) and bleeding in the hematological cancer patient subgroup. Risk factors associated with rVTE and bleeding were also explored. Methods CATCH (ClinicalTrials.govNCT01130025; Lee A et al. JAMA 2015) was a Phase III, multinational, randomized, active-controlled, open-label trial. Patients with solid tumors or hematological malignancies were randomized to receive therapeutic dosing of tinzaparin (175 IU/kg OD) vs warfarin (INR target 2.0 - 3.0) for treatment of acute VTE. Treatment was given for up to 6 months but was withheld during periods of severe thrombocytopenia (platelet count < 50 x 10 9/L). The primary efficacy outcome was the composite of symptomatic deep vein thrombosis (DVT), symptomatic nonfatal pulmonary embolism (PE), fatal PE, incidental proximal DVT and incidental proximal PE. All thrombosis and bleeding outcomes, including rPE, rDVT, major bleeding (MB), CRB, and CRNMB were objectively documented and centrally adjudicated in a treatment-blinded fashion. Patients with myeloma, lymphoma or leukemia were included in this sub-group analysis. Treatment effect was assessed by means of a cox-regression with time to first event as outcome and deaths not due to fatal PE as a competing risk factor. The cumulative incidence functions and the corresponding 95% CIs were estimated. Results 94 of 900 subjects (10.4%) in CATCH had a hematological cancer. Of these patients, 44 and 50 received tinzaparin and warfarin, respectively. The most common hematological cancer was lymphoma (59.6%), followed by myeloma (30.9%), chronic leukemia (5.3%) and acute leukemia (4.3%). rVTE occurred in fewer patients assigned to tinzaparin versus warfarin (2.4% vs 6.4%) but this difference was not statistically significant (HR 0.36; 95%CI 0.04-3.14). All recurrent thrombotic events were PE; no rDVT occurred. Also, trends for less bleeding with tinzaparin were noted for MB (tinzaparin 0.0% versus warfarin 5.0%), CRB (tinzaparin 10.4% vs warfarin 23.5%; HR 0.53; 95%CI 0.15-1.83) and CRNMB (tinzaparin 10.4% vs warfarin 19.5%; HR 0.69; 95%CI 0.19-2.51). 3 patients in each treatment arm had a fatal bleeding event and there was no difference in overall mortality (tinzaparin 22.7% vs warfarin 22.0%). There were no risk factors associated with rVTE identified. Factors associated with CRB in patients with hematological cancer included the use of antiplatelet agents (HR 7.63; 95%CI 1.17-49.6; p=0.033) and renal insufficiency (HR 12.4; 95%CI 2.15-72.0; p=0.005). Conclusion In this post-hoc subgroup analysis of patients with hematological cancers who received anticoagulation for acute VTE, tinzaparin may be a more effective and safer alternative to warfarin. Randomized controlled trials are warranted to test this hypothesis in this challenging population with a high risk of bleeding. Figure 1 Figure 1. Disclosures Lee: Leo Pharma: Consultancy, Honoraria; Bayer: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria; Servier: Consultancy, Honoraria. Bauersachs: Bayer: Honoraria, Speakers Bureau; BMS: Honoraria, Speakers Bureau; LEO Pharma: Honoraria, Speakers Bureau; Pfizer: Honoraria, Speakers Bureau. Janus: LEO Pharma: Current Employment. Leeder: LEO Pharma: Current Employment. Thoning: LEO Pharma: Current Employment. Khorana: Anthos: Consultancy, Honoraria; Halozyme: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Bayer: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Bristol Myers Squibb: Consultancy, Honoraria.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".